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Adaptor protein 180 (AP180) and its homolog, clathrin assembly lymphoid myeloid leukemia protein (CALM), are closely related proteins that play important roles in clathrin-mediated endocytosis. Here, we present the structure of the NH2-terminal domain of CALM bound to phosphatidylinositol-4,5- bisphosphate [PtdIns(4,5)P2] via a lysine-rich motif. This motif(More)
An unsupervised learning method is proposed for variable selection and its performance assessed using three typical QSAR data sets. The aims of this procedure are to generate a subset of descriptors from any given data set in which the resultant variables are relevant, redundancy is eliminated, and multicollinearity is reduced. Continuum regression, an(More)
We describe the use of Bayesian regularized artificial neural networks (BRANNs) coupled with automatic relevance determination (ARD) in the development of quantitative structure-activity relationship (QSAR) models. These BRANN-ARD networks have the potential to solve a number of problems which arise in QSAR modeling such as the following: choice of model;(More)
BCUT [Burden, CAS, and University of Texas] descriptors, defined as eigenvalues of modified connectivity matrices, have traditionally been applied to drug design tasks such as defining receptor relevant subspaces to assist in compound selections. In this paper we present studies of consensus neural networks trained on BCUTs to discriminate compounds with(More)
It has been shown that water solubility and octanol/water partition coefficient for a large diverse set of compounds can be predicted simultaneously using molecular descriptors derived solely from a two dimensional representation of molecular structure. These properties have been modelled using multiple linear regression, artificial neural networks and a(More)
A series of neural networks has been trained, using consensus methods, to recognize compounds that act at biological targets belonging to specific gene families. The MDDR database was used to provide compounds targeted against gene families and sets of randomly selected molecules. BCUT parameters were employed as input descriptors that encode structural(More)
Two QSAR models have been identified that predict the affinity and selectivity of arylpiperazinyl derivatives for alpha1 and alpha2 adrenoceptors (ARs). The models have been specified and validated using 108 compounds whose structures and inhibition constants (Ki) are available in the literature [Barbaro et al., J. Med. Chem., 44 (2001) 2118; Betti et al.,(More)
which gained a HEFCE RAE grade 5 in 2001, was formed in 1993 to provide joint facilities for research groups with requirements for high performance computing and acts as a focus for multidisciplinary research collaboration in topic areas of relevance to the life and chemical sciences. Professor Ford has received over £1.8 million of direct external funding(More)